Ronen Talmon Thesis

Ronen Talmon Thesis-45
Although it has its roots early in the last century, in recent years it has attracted considerable renewed interest from both theoretical and practical standpoints.Two prevalent types of data models are inherently related to the covariance matrix and are therefore of special interest in estimation problems.

Although it has its roots early in the last century, in recent years it has attracted considerable renewed interest from both theoretical and practical standpoints.Two prevalent types of data models are inherently related to the covariance matrix and are therefore of special interest in estimation problems.

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I have developed randomized algorithms for sequencing of DNA and RNA.

Paper: "A Random-Permutations-Based Approach to Fast Read Alignment" (RECOMB-SEQ 2013).

imaging of mixtures of different types of molecules.

I work on “” which represent heterogeneous molecules as higher-dimension objects.

The first of these is a latent linear factor model, also strongly related to PCA, which is manifested as a low rank component in the covariance matrix.

The second is undirected graphical model structure (Markov random field), which is related to presence of zeros in the inverse covariance (precision) matrix.

The movie below is an example of a reconstruction of a continuously heterogeneous object, using the approach described in this paper.

This is one of several approaches that I am developing for the heterogeneity problem in cryo-EM, and for other aspects of cryo-EM. See project webpage, this paper and in this report.

Also see this paper about the properties of DNA and sequencing.

Long-Range "Independence" The repetitive nature of DNA strings is one of the challenges in read alignment.

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